Some other works have employed semi-supervised learning. In [1]}, a network is trained to match the ensembled predictions of its own output obtained at different time intervals during training. Further, combination of adversarial training with semi-supervised techniques like entropy minimization [2]} and VAT [3]} have been explored in [4]}, [5]}.
